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BACKGROUNDS: Zygomatic implant (ZI) placement surgery is a viable surgical option for patients with severe maxillary atrophy and insufficient residual maxillary bone. Still, it is difficult and risky due to the long path of ZI placement and the narrow field of vision. Dynamic navigation is a superior solution, but it presents challenges such as requiring operators to have advanced skills and experience. Moreover, the precision and stability of manual implantation remain inadequate. These issues are anticipated to be addressed by implementing robot-assisted surgery and achieved by introducing a mixed reality (MR) navigation-guided hybrid robotic system for ZI placement surgery. METHODS: This study utilized a hybrid robotic system to perform the ZI placement surgery. Our first step was to reconstruct a virtual 3D model from preoperative cone-beam CT (CBCT) images. We proposed a series of algorithms based on coordinate transformation, which includes image-phantom registration, HoloLens-tracker registration, drill-phantom calibration, and robot-implant calibration, to unify all objects within the same coordinate system. These algorithms enable real-time tracking of the surgical drill's position and orientation relative to the patient phantom. Subsequently, the surgical drill is directed to the entry position, and the planned implantation paths are superimposed on the patient phantom using HoloLens 2 for visualization. Finally, the hybrid robot system performs the processed of drilling, expansion, and placement of ZIs under the guidance of the MR navigation system. RESULTS: Phantom experiments of ZI placement were conducted using 10 patient phantoms, with a total of 40 ZIs inserted. Out of these, 20 were manually implanted, and the remaining 20 were robotically implanted. Comparisons between the actual implanted ZI paths and the preoperatively planned ZI paths showed that our MR navigation-guided hybrid robotic system achieved a coronal deviation of 0.887 ± 0.213 mm, an apical deviation of 1.201 ± 0.318 mm, and an angular deviation of 3.468 ± 0.339° This demonstrates significantly better accuracy and stability than manual implantation. CONCLUSION: Our proposed hybrid robotic system enables automated ZI placement surgery guided by MR navigation, achieving greater accuracy and stability compared to manual operations in phantom experiments. Furthermore, this system is expected to apply to animal and cadaveric experiments, to get a good ready for clinical studies.
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Realidad Aumentada , Implantes Dentales , Procedimientos Quirúrgicos Robotizados , Cirugía Asistida por Computador , Animales , Humanos , Cirugía Asistida por Computador/métodos , Tomografía Computarizada de Haz Cónico , Prótesis e Implantes , Imagenología TridimensionalRESUMEN
Background/purpose: Augmented reality has been gradually applied in dental implant surgery. However, whether the dynamic navigation system integrated with augmented reality technology will further improve the accuracy is still unknown. The purpose of this study is to investigate the accuracy of dental implant placement using dynamic navigation and augmented reality-based dynamic navigation systems. Materials and methods: Thirty-two cone-beam CT (CBCT) scans from clinical patients were collected and used to generate 64 phantoms that were allocated to the augmented reality-based dynamic navigation (ARDN) group or the conventional dynamic navigation (DN) group. The primary outcomes were global coronal, apical and angular deviations, and they were measured after image fusion. A linear mixed model with a random intercept was used. A P value < 0.05 was considered to indicate statistical significance. Results: A total of 242 dental implants were placed in two groups. The global coronal, apical and angular deviations of the ARDN and DN groups were 1.31 ± 0.67 mm vs. 1.18 ± 0.59 mm, 1.36 ± 0.67 mm vs. 1.39 ± 0.55 mm, and 3.72 ± 2.13° vs. 3.1 ± 1.56°, respectively. No significant differences were found with regard to coronal and apical deviations (P = 0.16 and 0.6, respectively), but the DN group had a significantly lower angular deviation than the ARDN group (P = 0.02). Conclusion: The augmented reality-based dynamic navigation system yielded a similar accuracy to the conventional dynamic navigation system for dental implant placement in coronal and apical points, but the augmented reality-based dynamic navigation system yielded a higher angular deviation.
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PURPOSE: Reverse shoulder arthroplasty has demonstrated excellent clinical efficacy for patients with shoulder joint diseases and is increasingly in demand. Traditional surgery faces challenges such as limited exposed surfaces and a narrow field of vision, leading to a shorter prosthesis lifespan and a higher risk of complications. In this study, an optical navigation system was proposed to assist surgeons in real-time tracking of the surgical scene. METHODS: Our optical navigation system was developed using the NDI Polaris Spectra device and several open-source platforms. The first step involved using the preoperative medical image to plan screw implantation paths. Real-time tracking of the patient phantom or cadaver and the surgical instrument was achieved through registration and calibration algorithms. Surgeons were guided on drilling through visualization methods. Postoperative results were compared with the planned implantation paths, and an algorithm was introduced to correct errors caused by the incorrect beginning points. RESULTS: Experiments involved three scapula cadavers and their corresponding phantoms with identical anatomy. For each experiment, three holes were completed with drills with diameters of 3.2 mm and 8.0 mm, respectively. Comparisons between the postoperative actual screw implantation paths and the preoperative planned implantation paths revealed an entry error of 1.05 ± 0.15 mm and an angle error of 2.47 ± 0.55° for phantom experiments. For cadaver experiments, the entry error was 1.53 ± 0.22 mm, and the angle error was 4.91 ± 0.78°. CONCLUSION: Our proposed optical navigation system successfully achieved real-time tracking of the surgical site, encompassing the patient phantom or cadaver and surgical instrument, thereby aiding surgeons in achieving precise surgical outcomes. Future study will explore the integration of robots to further enhance surgical efficiency and effectiveness.
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In an emergency situation, fast and efficient logistics and distribution are essential for minimizing the impact of a disaster and for safeguarding property. When selecting a distribution center location, time satisfaction needs to be considered, in addition to the general cost factor. The improved jellyfish search algorithm (CIJS), which simulates the bionics of jellyfish foraging, is applied to solve the problem of an emergency logistics and distribution center site selection model considering time satisfaction. The innovation of the CIJS is mainly reflected in two aspects. First, when initializing the population, the two-level logistic map method is used instead of the original logistic map method to improve the diversity and uniform distribution of the population. Second, in the jellyfish search process, a Cauchy strategy is introduced to determine the moving distance of internal motions, which improves the global search capability and prevents the search from falling into local optimal solutions. The superiority of the improved algorithm was verified by testing 20 benchmark functions and applying them to site selection problems of different dimensions. The performance of the CIJS was compared to that of heuristic algorithms through the iterative convergence graph of the algorithm. The experimental results show that the CIJS has higher solution accuracy and faster solution speed than PSO, the WOA, and JS.
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Orthopedic surgery remains technically demanding due to the complex anatomical structures and cumbersome surgical procedures. The introduction of image-guided orthopedic surgery (IGOS) has significantly decreased the surgical risk and improved the operation results. This review focuses on the application of recent advances in artificial intelligence (AI), deep learning (DL), augmented reality (AR) and robotics in image-guided spine surgery, joint arthroplasty, fracture reduction and bone tumor resection. For the pre-operative stage, key technologies of AI and DL based medical image segmentation, 3D visualization and surgical planning procedures are systematically reviewed. For the intra-operative stage, the development of novel image registration, surgical tool calibration and real-time navigation are reviewed. Furthermore, the combination of the surgical navigation system with AR and robotic technology is also discussed. Finally, the current issues and prospects of the IGOS system are discussed, with the goal of establishing a reference and providing guidance for surgeons, engineers, and researchers involved in the research and development of this area.
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Procedimientos Ortopédicos , Robótica , Cirugía Asistida por Computador , Inteligencia Artificial , Cirugía Asistida por Computador/métodosRESUMEN
BACKGROUNDS: The key to successful dental implant surgery is to place the implants accurately along the pre-operative planned paths. The application of surgical navigation systems can significantly improve the safety and accuracy of implantation. However, the frequent shift of the views of the surgeon between the surgical site and the computer screen causes troubles, which is expected to be solved by the introduction of mixed-reality technology through the wearing of HoloLens devices by enabling the alignment of the virtual three-dimensional (3D) image with the actual surgical site in the same field of view. METHODS: This study utilized mixed reality technology to enhance dental implant surgery navigation. Our first step was reconstructing a virtual 3D model from pre-operative cone-beam CT (CBCT) images. We then obtained the relative position between objects using the navigation device and HoloLens camera. Via the algorithms of virtual-actual registration, the transformation matrixes between the HoloLens devices and the navigation tracker were acquired through the HoloLens-tracker registration, and the transformation matrixes between the virtual model and the patient phantom through the image-phantom registration. In addition, the algorithm of surgical drill calibration assisted in acquiring transformation matrixes between the surgical drill and the patient phantom. These algorithms allow real-time tracking of the surgical drill's location and orientation relative to the patient phantom under the navigation device. With the aid of the HoloLens 2, virtual 3D images and actual patient phantoms can be aligned accurately, providing surgeons with a clear visualization of the implant path. RESULTS: Phantom experiments were conducted using 30 patient phantoms, with a total of 102 dental implants inserted. Comparisons between the actual implant paths and the pre-operatively planned implant paths showed that our system achieved a coronal deviation of 1.507 ± 0.155 mm, an apical deviation of 1.542 ± 0.143 mm, and an angular deviation of 3.468 ± 0.339°. The deviation was not significantly different from that of the navigation-guided dental implant placement but better than the freehand dental implant placement. CONCLUSION: Our proposed system realizes the integration of the pre-operative planned dental implant paths and the patient phantom, which helps surgeons achieve adequate accuracy in traditional dental implant surgery. Furthermore, this system is expected to be applicable to animal and cadaveric experiments in further studies.
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BACKGROUND: This in vitro study aims to evaluate the accuracy of dental implant placement by a novel image-guided hybrid robotic system for dental implant surgery (HRS-DIS). METHODS: The HRS-DIS with a 5 degree of freedom (DOF) serial manipulator and a 6 DOF Stewart platform was developed. To evaluate the accuracy of repeated drilling, the holes were prepared twice with a 2.2 mm drill. To evaluate the accuracy of dental implant placement, the entry, exit and angle deviations of dental implants were measured. RESULTS: Twenty-four holes were prepared twice, and mean (±SD) of diameters were measured as 2.2 ± 0.02 mm. A total of 160 dental implants were placed in 32 phantoms by HRS-DIS. The mean (±SD) of the entry, exit and angle deviation were 0.8 ± 0.54 mm, 0.87 ± 0.54 mm and 1.0 1 ± 0.44°, respectively. CONCLUSIONS: The results of the in vitro study preliminarily validated that the HRS-DIS could provide a high accuracy for dental implant surgery.
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Implantes Dentales , Procedimientos Quirúrgicos Robotizados , Cirugía Asistida por Computador , Humanos , Cirugía Asistida por Computador/métodos , Proyectos de Investigación , Implantación Dental Endoósea , Diseño Asistido por Computadora , Tomografía Computarizada de Haz Cónico/métodos , Imagenología TridimensionalRESUMEN
OBJECTIVES: To compare the accuracy of dental implant placement using a dynamic navigation and a robotic system. METHODS: Eighty three-dimensional (3D) printed phantoms, including edentulous and partially edentulous jaws, were assigned to two groups: a dynamic navigation system (Beidou-SNS) group and a robotic system (Hybrid Robotic System for Dental Implant Surgery, HRS-DIS) group. The entry, exit and angle deviations of the implants in 3D world were measured after pre-operative plans and postoperative cone-beam computed tomography (CBCT) fusion. A linear mixed model with a random intercept was applied, and a p value <.05 was considered statistically significant. RESULTS: A total of 480 implants were placed in 80 phantoms. The comparison deviation of the dynamic navigation system and robotic system groups showed a mean (± SD) entry deviation of 0.96 ± 0.57 mm vs. 0.83 ± 0.55 mm (p=0.04), a mean exit deviation of 1.06 ± 0.59 mm vs. 0.91 ± 0.56 mm (p=0.04), and a mean angle deviation of 2.41± 1.42° vs. 1 ± 0.48° (p<0.00). CONCLUSIONS: The implant positioning accuracy of the robotic system was superior to that of the dynamic navigation system, suggesting that this prototype robotic system (HRS-DIS) could be a promising tool in dental implant surgery. CLINICAL SIGNIFICANCE: This in vitro study is of clinical interest because it preliminarily shows that a robotic system exhibits lower deviations of dental implants than a dynamic navigation system, in dental implant surgery, in both partially and completely edentulous jaws. Further clinical studies are needed to evaluate the current results.